Simple Ways to Take Gender Bias Out of Your Jobs

HBS Career & Professional Development (CPD) is sharing Working Knowledge articles to further educate our recruiting partners about best practices in human resources.

In the Quest for Gender Equality, Job Ads Are Low-hanging Fruit; an
Interview by Carmen Nobel

Here’s a hint for employers wondering why mostly men (or mostly women) are applying for your company’s open positions. Look at the language in your job listings. Chances are, the wording is more biased toward one gender than you realize.

While the Civil Rights Act of 1964 prohibits employers from overtly soliciting a preferred gender in their job listings, research shows that the language of job descriptions often subtly adheres to gender stereotypes. And that deters members of the opposite gender from applying to those jobs.

For example, a few years ago, social scientists at the University of Waterloo and Duke University coded a long list of adjectives and verbs as masculine or feminine then scanned a popular job site to look for those words. They found that job ads in male-dominated fields (like software programming) tended to use masculine-coded words such as “competitive” and “dominate” much more than job ads in female-dominated fields. Follow-up research confirmed such words made those job listings less appealing to women.

Yet so-called “gendered language” continues to run rampant in online employment listings. Consider the word “ninja,” which increasingly appears in job descriptions in high tech. Among the listings on the employment-related search engine Indeed.com, usage of “ninja” increased nearly 400 percent between January 2012 and October 2016, according to the company’s Job Trends database tool. While the word may make the job sound exciting, it may also dissuade women from applying, as society tends to regard “ninja” as masculine. The word “dominant” rose by 65 percent in the same time period.

It’s unlikely that the world will stop associating certain words with certain genders any time soon. Fortunately for employers looking to narrow the applicant-pool gender gap, there is a simple way to take the gender bias out of job listings: Simply rewrite them.

“Our minds are stubborn beasts that are hard to change, but it’s not hard to de-bias the application process,” says behavioral economist Iris Bohnet, a visiting professor at Harvard Business School, co-chair of Harvard’s Behavioral Insights Group, and director of the Women and Public Policy Program at Harvard Kennedy School. She is the author of the book What Works: Gender Equality by Design, which discusses how organizations can leverage findings of behavioral science research to fight gender bias in the workplace.

“The idea of the book and of my research is to say that it’s easier to de-bias organizations’ practices and procedures than to de-bias mindsets,” she says. “To start with, job ads are super-low-hanging fruit.”

Purging the gendered language

There are two easy key ways to take the gender bias out of job ads, Bohnet says: One, purge the gendered language. Two, limit the number of mandatory qualifications to apply for the job.

In What Works, she cites the example of an elementary school advertising for “a committed teacher with exceptional pedagogical and interpersonal skills to work in a supportive, collaborative work environment.” The potential problem is that “supportive,” “collaborative” and even “committed” are widely associated with femininity, which may detract men from applying.

“Maybe elementary schools want to add still more women to their roughly 80 to 90 percent female faculty,” she writes. “But, I doubt it. Most schools want to benefit from 100 percent of the talent pool and not deter skilled male applicants simply because the gendered adjectives in their advertisements signal to men that they do not belong.”

The easy fix: Nix “supportive” and “collaborative” from the job description. “With a few simple word-choice changes—‘they look for an excellent teacher with exceptional pedagogical skills’—you have expanded the potential talent pool,” she writes.

Bohnet does not mean to imply that men lack the ability to be supportive or collaborative, a point she stresses when discussing the book during a recent interview in her HBS office. “Of course men can be supportive and collaborative, caring and warm,” she says. “But, based on data analytics on the kinds of jobs men and women apply for, research shows that the adjectives matter.”

Limiting the number of qualifications in a job description is another important way to mitigate job-listing gender bias. Bohnet recommends listing only the skills that are absolutely necessary for the role. Often, job descriptions are designed by a committee of opinionated individuals, resulting in a long laundry list of qualifications, some of which are vital, but many of which are just nice-to-haves. Here’s the problem with that list of nice-to-haves: “Many women won’t apply for a job unless they meet almost all of the listed requirements,” Bohnet says. “Men tend to have a lower threshold for applying.”

Lessons from the classroom and tools for the real world

During the past semester, Bohnet taught a graduate-level course called “Behavioral Economics for Organizations,” jointly listed at HBS and the Harvard Kennedy School. Like her book, the course uses social science research and tools, in this case to promote overall organizational health. In one of the lessons, students were tasked with using behavioral design to de-bias talent management; in another, to promote ethics and compliance in organizations.

Guest speakers in her class included Aniela Unguresan, co-founder of the EDGE Certified Foundation, which developed an assessment methodology and business certification standard for gender equality, and Anka Wittenberg, chief diversity officer of technology giant SAP. In addition to becoming one of the first companies to receive EDGE certification, SAP recently announced plans to add de-biasing capabilities to its Success Factors line of human resources software, including the ability to flag job descriptions for potentially biased language.

The course’s guest speakers also included the CEOs of startups Applied Ltd. and Unitive, both of which use behavioral science research to help organizations take the gender bias out of all steps of the employee recruitment process—including writing a job description, evaluating applications, and interviewing applicants.

Bohnet notes that there are also free online tools that automatically scan job descriptions for biased language, such as Gender Decoder for Job Ads. Simply paste the text of a job listing into the decoder, and it scans the text for the list of gender-coded words from the Duke/Waterloo study. In less than a second, the decoder reports whether there are more masculine-coded or feminine-coded words in the ad. It’s not all encompassing—it doesn’t include “ninja,” for example. But, it’s a good start, it’s free, and easy to use.

“There’s a cool story going on,” Bohnet says. “It says, here’s the research, and here are the tools you can use to apply it at work.”

Note to readers: Bohnet and colleagues are currently conducting experimental field research in which they post and track different versions of the same job listing, adjusting the language to gauge how and whether it affects who applies for the job. If your company might be a good fit for this line of research, please reach out to Bohnet at ibohnet@hbs.edu or iris_bohnet@harvard.edu